Evaluation of Extra-Prostatic Extension on Deep Learning-Reconstructed High-Resolution Thin-Slice T2-Weighted Images...

The aim of this study was to compare diagnostic performance for extra-prostatic extension (EPE) and image quality among three image datasets: conventional T2-weighted images (T2WI_conv, slice thickness, 3 mm) and high-resolution thin-slice T2WI (T2WI_HR, 2 mm), with and without deep learning reconstruction (DLR) in patients with prostatic cancer (PCa). A total of 88 consecutive patients (28 EPE-positive and 60 negative) diagnosed with PCa via radical prostatectomy who had undergone 3T-MRI were included. Two independent reviewers performed a crossover review in three sessions, in which each reviewer recorded five-point confidence scores for the presence of EPE and image quality using a five-point Likert scale. Pathologic topographic maps served as the reference standard. For both reviewers, T2WI_conv showed better diagnostic performance than T2WI_HR with and without DLR (AUCs, in order, for reviewer 1, 0.883, 0.806, and 0.772, p = 0.0006; for reviewer 2, 0.803, 0.762, and 0.745, p = 0.022). The image quality was also the best in T2WI_conv, followed by T2WI_{HR with DLR} and T2WI_{HR without DLR} for both reviewers (median, in order, 3, 4, and 5, p < 0.0001). In conclusion, T2WI_conv was optimal in regard to image quality and diagnostic performance for the evaluation of EPE in patients with PCa.